According to [1]}, the idea of deep unfolding can be summarized as “... given a model-based approach
that requires an iterative inference method, we unfold the iterations into a layer-wise structure analogous to a DNN. We then untie the model parameters across layers to obtain novel neural-network-like architectures that can easily be trained discriminatively using gradient-based methods.”
